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1. 发明公开

US20240017766A1 SYSTEM AND METHOD FOR REINFORCEMENT LEARNING OF STEERING GEOMETRY 审中-公开
公开(公告)号：US20240017766A1
公开(公告)日：2024-01-18
申请号：US18258375
申请日：2020-12-21
申请人： VOLVO TRUCK CORPORATION
发明人： Chidambaram SUBRAMANIAN
IPC分类号： B62D17/00 , B60G17/016
CPC分类号： B62D17/00 , B60G17/0163 , B60G2200/4622 , B60G2600/187
摘要： Systems, methods, and computer-readable storage media for adjusting the steering geometry of a vehicle by using reinforcement learning in series with a neural network to determine when and how to adjust the steering geometry of the vehicle. A system can do this by receiving vehicle information associated with ongoing movement of the vehicle, and executing a reinforcement learning model using that vehicle information. The outputs of the reinforcement learning model can include a current driving cycle of the vehicle and a current application of the vehicle. The system then executes a machine learning model, where inputs to the machine learning model can include the outputs of the reinforcement learning model and the vehicle information. The outputs of the machine learning model can then include a wheel alignment signal.

2. 发明公开

US20230356556A1 SYSTEM AND METHOD FOR TIRE CONTACT PATCH OPTIMIZATION 审中-公开
公开(公告)号：US20230356556A1
公开(公告)日：2023-11-09
申请号：US18044851
申请日：2020-11-23
申请人： VOLVO TRUCK CORPORATION
发明人： Chidambaram SUBRAMANIAN
IPC分类号： B60G17/0195 , B60C23/00 , B60G17/0165 , B60G17/052
CPC分类号： B60G17/0195 , B60C23/002 , B60G17/0165 , B60G17/052 , B60C2019/004
摘要： Systems, methods, and computer-readable storage media for using multi-stage machine learning algorithms to optimize tire contact patches on a vehicle. Vehicle sensors first collect vehicle information for the vehicle, and input that data into a first machine learning algorithm. The first machine learning algorithm then outputs a lateral dimension, a longitudinal dimension, and a diagonal dimension, which together identify a tire contact patch of at least one tire on the vehicle. The operator of the vehicle provides a human preference for how the vehicle operates, and a second machine learning algorithm is executed. The second machine learning algorithm inputs can include the plurality of vehicle information, the first machine learning algorithm outputs, and the human preference, and the second machine learning algorithm outputs can include a desired tire pressure of the at least one tire and an air suspension adjustment for the normal load of the vehicle.

3. 发明公开

US20240190446A1 TYRE ROLLING RESISTANCE ESTIMATION BASED ON A DYNAMIC TYRE MODEL 审中-公开
公开(公告)号：US20240190446A1
公开(公告)日：2024-06-13
申请号：US18554004
申请日：2021-04-07
申请人： VOLVO TRUCK CORPORATION
发明人： Leo LAINE , Leon HENDERSON , Ulf STENBRATT , Adithya ARIKERE , Chidambaram SUBRAMANIAN
IPC分类号： B60W40/12 , B60C99/00 , B60W10/22 , B60W30/18 , G07C5/10
CPC分类号： B60W40/12 , B60C99/006 , B60W10/22 , B60W30/18009 , G07C5/10 , B60W2520/26 , B60W2520/28 , B60W2530/16 , B60W2530/20 , B60W2555/20 , B60W2556/10 , B60W2556/50
摘要： A method for controlling motion of a heavy-duty vehicle includes obtaining input data related to one or more tire parameters of a tire on the heavy-duty vehicle, estimating at least part of the one or more tire parameters based on the input data, configuring a tire model, wherein the tire model defines a relationship between tire wheel rolling resistance and vehicle motion state, wherein the tire model is parameterized by the one or more tire parameters, estimating vehicle motion state, and controlling motion of the heavy-duty vehicle based on the tire model and on the vehicle motion state.

4. 发明公开

US20240182041A1 IMPROVED VEHICLE MOTION MANAGEMENT BASED ON A DYNAMIC TIRE MODEL 审中-公开
公开(公告)号：US20240182041A1
公开(公告)日：2024-06-06
申请号：US18285092
申请日：2021-04-07
申请人： Volvo Truck Corporation
发明人： Leo LAINE , Leon HENDERSON , Ulf STENBRATT , Adithya ARIKERE , Mats RYDSTRÖM , Chidambaram SUBRAMANIAN
IPC分类号： B60W40/101 , B60C23/04 , B60C99/00 , B60W30/18 , B60W40/10
CPC分类号： B60W40/101 , B60C23/0488 , B60C99/006 , B60W30/18172 , B60W40/1005 , B60C2200/06 , B60W2300/12 , B60W2510/18 , B60W2520/06 , B60W2520/10 , B60W2520/20 , B60W2520/26 , B60W2520/28 , B60W2520/30 , B60W2530/10 , B60W2530/16 , B60W2530/20 , B60W2555/20 , B60W2556/10 , B60W2556/50
摘要： A method for controlling motion of a heavy-duty vehicle, the method including:

obtaining input data related to one or more parameters of a tire on the heavy-duty vehicle,
determining at least part of the one or more tire parameters based on the input data,
configuring a tire model, wherein the tire model defines a relationship between wheel slip and generated wheel force, wherein the tire model is parameterized by the one or more tire parameters, and
controlling the motion of the heavy-duty vehicle based on the relationship between wheel slip and generated wheel force.

5. 发明申请

US20230026361A1 METHOD FOR ESTIMATING A BRAKE FACTOR PARAMETER IN A BRAKING SYSTEM, AND VEHICLE IMPLEMENTING THE SAME 有权
公开(公告)号：US20230026361A1
公开(公告)日：2023-01-26
申请号：US17862270
申请日：2022-07-11
申请人： Volvo Truck Corporation
发明人： Chidambaram SUBRAMANIAN
IPC分类号： B60T8/172 , B60T8/171
摘要： Method for estimating a brake factor parameter, the brake factor parameter being defined as a ratio of a braking torque over a braking pressure, the braking torque being applied on a wheel of a vehicle by a braking wheel sub-system of a braking system of the vehicle, the braking pressure being applied by the braking wheel sub-system to achieve the braking torque on the wheel of the vehicle, the method comprising collecting input parameters and estimating the brake factor parameter as a function of the at least one input parameter, an output of the step of estimating being an open loop estimation of the brake factor parameter.

6. 发明公开

US20240116565A1 SYSTEM AND METHOD FOR DYNAMIC ACKERMAN CONTROL 审中-公开
公开(公告)号：US20240116565A1
公开(公告)日：2024-04-11
申请号：US18546212
申请日：2021-03-17
申请人： Chidambaram SUBRAMANIAN , VOLVO TRUCK CORPORATION
发明人： Chidambaram SUBRAMANIAN
IPC分类号： B62D6/00 , B62D7/09 , B62D7/14
CPC分类号： B62D6/002 , B62D7/09 , B62D7/144
摘要： Systems, methods, and computer-readable storage media for a dynamic Ackermann geometry control system. The system receives, at a processor aboard a tractor of an articulated vehicle, vehicle information associated with ongoing movement of the articulated vehicle as well as a driver optimization preference. The system then executes an Ackerman control algorithm, with inputs such as the vehicle information and/or at least one feedback item. The outputs of the Ackerman control algorithm can include estimations of tire forces for each tire of the articulated vehicle and estimations of cornering characteristics of the articulated vehicle. The system then calculates, based on the estimations of tire forces and based on the estimations of cornering characteristics, a desired Ackerman geometry for the articulated vehicle. The system then transmits a command to modify a turning angle associated with at least one wheel of the articulated vehicle.

7. 发明公开

US20230334435A1 COMMERCIAL VEHICLES ROTOR CRACKING PREDICTION USING RECURRENT NEURAL NETWORK 审中-公开
公开(公告)号：US20230334435A1
公开(公告)日：2023-10-19
申请号：US18043202
申请日：2020-09-10
申请人： VOLVO TRUCK CORPORATION
发明人： Chidambaram SUBRAMANIAN
IPC分类号： G06Q10/20 , B60T17/22
CPC分类号： G06Q10/20 , B60T17/22
摘要： Systems, methods, and computer-readable storage media for training a Recurrent Neural Network to evaluate sensor data related to a brake rotor, then diagnosing brake rotors using sensor data and the trained Recurrent Neural Network. Sensor data can include audio data, temperature data, caliper pressure data, and/or any other data related to operation of the brake rotor being evaluated. When a processor is configured to execute the trained Recurrent Neural Network, sensor inputs can be provided to the processor, with the output being a diagnosis of the brake rotor state.

8. 发明公开

US20230242126A1 METHOD FOR RATING AND FOR IMPROVING A DRIVER'S DRIVING STYLE BASED ON A SAFETY LEVEL CRITERIA 审中-公开
公开(公告)号：US20230242126A1
公开(公告)日：2023-08-03
申请号：US18047403
申请日：2022-10-18
申请人： VOLVO TRUCK CORPORATION
发明人： Chidambaram SUBRAMANIAN
IPC分类号： B60W40/09 , G06N3/044 , G07C5/00
CPC分类号： B60W40/09 , G06N3/044 , G07C5/008 , B60W2556/45
摘要： An electronic control unit is configured to collect and process sensor data comprising environment data, driver signals and vehicle state signals by a physics-based processing module the sensor data to produce a physics-based route classification and a physics-based driver's driving style classification, and by a neural network module trained for predicting a machine learning route classification and a machine learning driver's driving style classification; provide the physics-based route classification and the physics-based driver's driving style classification, and the machine learning route classification and the machine learning driver's driving style classification, to a feedback module configured to estimate a driving recommendation for the driver; provide emulated driver signals, based on the driving recommendation, and the environment data, to a vehicle simulation module to provide simulated vehicle state signals; process by the physics-based processing module the emulated driver signals and the simulated vehicle state signals and the environment data, to produce a simulated physics-based route classification and a simulated physics-based driver's driving style classification, and by the neural network module to predict a simulated machine learning route classification and a simulated machine learning driver's driving style classification; check with the feedback module whether the driving recommendation has improved the safety level, and provide the driving recommendation to the driver if the driver's driving style safety level was improved.

9. 发明申请

US20230029704A1 METHOD FOR DETECTING A FAILURE IN A VEHICLE PNEUMATIC SYSTEM 有权
公开(公告)号：US20230029704A1
公开(公告)日：2023-02-02
申请号：US17862523
申请日：2022-07-12
申请人： Volvo Truck Corporation
发明人： Chidambaram SUBRAMANIAN
IPC分类号： B60T8/88 , G01M3/26 , B60T17/22
摘要： Method for detecting a failure in a pneumatic system of a vehicle, the pneumatic system comprising a supply pneumatic subsystem comprising supply lines, a control pneumatic subsystem comprising control lines, a delivery pneumatic subsystem comprising delivery lines, the vehicle comprising an electronic control unit configured to implement a trained supply recurrent neural network, a trained control recurrent neural network, a trained delivery recurrent neural network, and a trained main recurrent neural network; the method comprising collect and provide the input parameters to the trained recurrent neural networks to get a output from recurrent neural networks; provide the input parameters and the output parameters from recurrent neural networks to get a main output indicative of a pneumatic system health parameter indicative of a presence or an absence of a failure in one of the supply pneumatic subsystem, or the control pneumatic subsystem, or the delivery pneumatic subsystem of the pneumatic system.

10. 发明公开

US20240367639A1 TYRE WEAR RATE ESTIMATION BASED ON A DYNAMIC TYRE MODEL 审中-公开
公开(公告)号：US20240367639A1
公开(公告)日：2024-11-07
申请号：US18554048
申请日：2021-04-07
申请人： VOLVO TRUCK CORPORATION
发明人： Leo LAINE , Leon HENDERSON , Ulf STENBRATT , Adithya ARIKERE , Chidambaram SUBRAMANIAN
IPC分类号： B60W30/02 , G01M17/02
CPC分类号： B60W30/02 , G01M17/02 , B60W2520/26 , B60W2530/20 , B60W2555/20
摘要： A method for controlling motion of a heavy-duty vehicle includes obtaining input data related to one or more tire parameters of a tire on the heavy-duty vehicle, estimating at least part of the one or more tire parameters based on the input data, configuring a tire model, wherein the tire model defines a relationship between tire wear rate and vehicle motion state, wherein the tire model is parameterized by the one or more tire parameters, estimating vehicle motion state, and controlling motion of the heavy-duty vehicle based on the tire model and on the vehicle motion state.

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